Automatic Generation of Artificial Space Weather Forecast Product Based on Sequence-to-sequence Model

Both analyzing a large amount of space weather observed data and alleviating personal experience bias are significant challenges in generating artificial space weather forecast products.With the use of natural language generation methods based on the sequence-to-sequence model,space weather forecast texts can be automatically generated.To conduct our generation tasks at a fine-grained level,a taxonomy of space weather phenomena based on descriptions is presented.Then,our MDH(Multi-Domain Hybrid)model is proposed for generating space weather summaries in two stages.This model is composed of three sequence-to-sequence-based deep neural network sub-models(one Bidirectional Auto-Regressive Transformers pre-trained model and two Transformer models).Then,to evaluate how well MDH performs,quality evaluation metrics based on two prevalent automatic metrics and our innovative human metric are presented.The comprehensive scores of the three summaries generating tasks on testing datasets are 70.87,93.50,and 92.69,respectively.The results suggest that MDH can generate space weather summaries with high accuracy and coherence,as well as suitable length,which can assist forecasters in generating high-quality space weather forecast products,despite the data being starved.

Latest Scientific Results of China's Lunar and Deep Space Exploration(2022–2024)

China has successfully launched six lunar probes so far.From Chang'E-1 to Chang'E-4,they completed the circling,landing and roving exploration,of which Chang'E-4 was the first landing on the far side of the Moon in human history.Chang'E-5 was launched in December 2020,bringing back 1731 g of lunar soil samples.Through the detailed analysis of the samples,the scientists understand the history of late lunar volcanism,specifically extending lunar volcanism by about 800 million to 1 billion years,and proposed possible mechanisms.In addition,there are many new understandings of space weathering such as meteorite impacts and solar wind radiation on the Moon.China's first Mars exploration mission Tianwen-1 was successfully launched in July 2021.Through the study of scientific data,a number of important scientific achievements have been made in the topography,water environment and shallow surface structure of Mars.This paper introduces the main scientific achievements of Chang'E-4,Chang'E-5 and Tianwen-1 in the past two years,excluding technical and engineering contents.Due to the large number of articles involved,this paper only introduces part of the results.

Ultrasound-Guided Superior Gluteal Nerve Hydrodissection in the Treatment of Deep Gluteal Syndrome

Background: Deep gluteal syndrome is a common cause of posterior hip pain. It results from peripheral nerves, such as the sciatic or superior gluteal nerve, being compressed in the deep gluteal space. Hydrodissection is a novel technique for the treatment of nerve pain due to entrapment. The use of hydrodissection for the treatment of deep gluteal syndrome has not been reported. Methods: A case report involved a 42-year-old female presenting with deep gluteal syndrome. Case report: We report, with patient consent, an ultrasound-guided superior gluteal nerve hydrodissection method used for treating the deep gluteal syndrome. A previously healthy 42-year-old female patient sought medical attention due to persistent left gluteal pain. Trials of joint injections, physiotherapy, and epidural blocks were unsuccessful. Hydrodissection under ultrasound-guidance allowed separation of the fascial plane in areas with significant neural innervation. We targeted the superior gluteal nerve with hydrodissection offering the patient immediate and persistent relief from her symptoms. Conclusion: Ultrasound-guided hydrodissection of the superior gluteal nerve offers an effective and novel diagnostic and treatment option for deep gluteal syndrome.

Research Progress on the Solder Joint Reliability of Electronics Using in Deep Space Exploration

The spacecraft for deep space exploration missions will face extreme environments,including cryogenic temperature,intense radiation,wide-range temperature variations and even the combination of conditions mentioned above.Harsh environments will lead to solder joints degradation or even failure,resulting in damage to onboard electronics.The research activities on high reliability solder joints using in extreme environments can not only reduce the use of onboard protection devices,but effectively improve the overall reliability of spacecraft,which is of great significance to the aviation industry.In this paper,we review the reliability research on SnPb solder alloys,Sn-based lead-free solder alloys and In-based solder alloys in extreme environments,and try to provide some suggestions for the follow-up studies,which focus on solder joint reliability under extreme environments.

Heterogeneous information phase space reconstruction and stability prediction of filling body–surrounding rock combination

Traditional research believes that the filling body can effectively control stress concentration while ignoring the problems of unknown stability and the complex and changeable stress distribution of the filling body–surrounding rock combination under high-stress conditions.Current monitoring data processing methods cannot fully consider the complexity of monitoring objects,the diversity of monitoring methods,and the dynamics of monitoring data.To solve this problem,this paper proposes a phase space reconstruction and stability prediction method to process heterogeneous information of backfill–surrounding rock combinations.The three-dimensional monitoring system of a large-area filling body–surrounding rock combination in Longshou Mine was constructed by using drilling stress,multipoint displacement meter,and inclinometer.Varied information,such as the stress and displacement of the filling body–surrounding rock combination,was continuously obtained.Combined with the average mutual information method and the false nearest neighbor point method,the phase space of the heterogeneous information of the filling body–surrounding rock combination was then constructed.In this paper,the distance between the phase point and its nearest point was used as the index evaluation distance to evaluate the stability of the filling body–surrounding rock combination.The evaluated distances(ED)revealed a high sensitivity to the stability of the filling body–surrounding rock combination.The new method was then applied to calculate the time series of historically ED for 12 measuring points located at Longshou Mine.The moments of mutation in these time series were at least 3 months ahead of the roadway return dates.In the ED prediction experiments,the autoregressive integrated moving average model showed a higher prediction accuracy than the deep learning models(long short-term memory and Transformer).Furthermore,the root-mean-square error distribution of the prediction results peaked at 0.26,thus outperforming the no-prediction method in 70%of the cases.

Reliable transmission of consultative committee for space data systems file delivery protocol in deep space communication

In consultative committee for space data systems（CCSDS） file delivery protocol（CFDP） recommendation of reliable transmission,there are no detail transmission procedure and delay calculation of prompted negative acknowledge and asynchronous negative acknowledge models.CFDP is designed to provide data and storage management,story and forward,custody transfer and reliable end-to-end delivery over deep space characterized by huge latency,intermittent link,asymmetric bandwidth and big bit error rate（BER）.Four reliable transmission models are analyzed and an expected file-delivery time is calculated with different trans-mission rates,numbers and sizes of packet data units,BERs and frequencies of external events,etc.By comparison of four CFDP models,the requirement of BER for typical missions in deep space is obtained and rules of choosing CFDP models under different uplink state informations are given,which provides references for protocol models selection,utilization and modification.

Application of the sun line-of-sight vector in the optimal attitude estimation of deep-space probe

This paper proposed an optimal algorithm using the sun line-of-sight vector to improve the probe attitude estimation accuracy in deep-space mission.Firstly,the elaborate analysis of the attitude estimation error from vector observations was done to demonstrate that the geometric relation between the reference vectors is an important factor which influences the accuracy of attitude estimation.Then,with introduction of the sun line-of-sight vector,the attitude quaternion obtained from the star-sensor was converted into a pair of mutually perpendicular reference vectors perpendicular to the sun vector.The normalized weights were calculated according to the accuracy of the sensors.Furthermore,the optimal attitude estimation in the least squares sense was achieved with the quaternion estimation method.Finally,the results of simulation demonstrated the validity of the proposed optimal algorithm based on the practical data of the Deep Impact mission.

基于DeeplabV3+网络的轻量化语义分割算法

针对传统语义分割模型参数量大、计算速度慢且效率不高等问题,改进一种基于DeeplabV3+网络的轻量化语义分割模型Faster-DeeplabV3+。Faster-DeeplabV3+模型采用轻量级MobilenetV2代替Xception作为主干特征提取网络,大幅减少参数量,提高计算速度;引入深度可分离卷积(deep separable convolution, DSC)与空洞空间金字塔(atrous spatia pyramid pooling, ASPP)中的膨胀卷积设计成新的深度可分离膨胀卷积(depthwise separable dilated convolution, DSD-Conv),即组成深度可分离空洞空间金字塔模块(DP-ASPP),扩大感受野的同时减少原本卷积参数量,提高运算速度;加入改进的双注意力机制模块分别对编码区生成的低级特征图和高级特征图进行处理,增强网络对不同维度特征信息提取的敏感性和准确性;融合使用交叉熵和Dice Loss两种损失函数,为模型提供更全面、更多样的优化。改进模型在PASCAL VOC 2012数据集上进行测试。实验结果表明:平均交并比由76.57%提升至79.07%,分割准确度由91.2%提升至94.3%。改进模型的网络参数量(params)减少了3.86×10~6,浮点计算量(GFLOPs)减少了117.98 G。因此,Faster-DeeplabV3+算法在大幅降低参数量、提高运算速度的同时保持较高语义分割效果。

A SURVEY OF DEEP SPACE COMMUNICATIONS

Deep space communications has played an important role in deep space exploration. Compared with common satellite and terrestrial communications, deep space communications faces more challenging environment. The paper investigated the unique features of deep space communica-tions in detail, discussed the key technologies and its development trends for deep space communica-tions.

A Footpad Structure with Reusable Energy Absorption Capability for Deep Space Exploration Lander:Design and Analysis

The footpad structure of a deep space exploration lander is a critical system that makes the initial contact with the ground,and thereby plays a crucial role in determining the stability and energy absorption characteristics during the impact process.The conventional footpad is typically designed with an aluminum honeycomb structure that dissipates energy through plastic deformation.Nevertheless,its effectiveness in providing cushioning and energy absorption becomes significantly compromised when the structure is crushed,rendering it unusable for reusable landers in the future.This study presents a methodology for designing and evaluating structural energy absorption systems incorporating recoverable strain constraints of shape memory alloys(SMA).The topological configuration of the energy absorbing structure is derived using an equivalent static load method(ESL),and three lightweight footpad designs featuring honeycomb-like Ni-Ti shape memory alloys structures and having variable stiffness skins are proposed.To verify the accuracy of the numerical modelling,a honeycomb-like structure subjected to compression load is modeled and then compared with experimental results.Moreover,the influence of the configurations and thickness distribution of the proposed structures on their energy absorption performance is comprehensively evaluated using finite element simulations.The results demonstrate that the proposed design approach effectively regulates the strain threshold to maintain the SMA within the constraint of maximum recoverable strain,resulting in a structural energy absorption capacity of 362 J/kg with a crushing force efficiency greater than 63%.

Mitigating Deep Dielectric Charging Effects at the Orbits of Jovian Planets

Deep dielectric charging/discharging,caused by high energy electrons,is an important consideration in electronic devices used in space environments because it can lead to spacecraft anomalies and failures.The Jovian planets,including Saturn,Uranus,Neptune and Jupiter’s moons,are believed to have robust electron radiation belts at relativistic energies.In particular,Jupiter is thought to have caused at least 42 internal electrostatic discharge events during the Voyager 1 flyby.With the development of deep space exploration,there is an increased focus on the deep dielectric charging effects in the orbits of Jovian planets.In this paper,GEANT4,a Monte Carlo toolkit,and radiation-induced conductivity(RIC)are used to calculate deep dielectric charging effects for Jovian planets.The results are compared with the criteria for preventing deep dielectric charging effects in Earth orbit.The findings show that effective criteria used in Earth orbit are not always appropriate for preventing deep dielectric charging effects in Jovian orbits.Generally,Io,Europa,Saturn(R_S=6),Uranus(L=4.73)and Ganymede missions should have a thicker shield or higher dielectric conductivity,while Neptune(L=7.4)and Callisto missions can have a thinner shield thickness or a lower dielectric conductivity.Moreover,dielectrics grounded with double metal layers and thinner dielectrics can also decrease the likelihood of discharges.

A NOVEL APPROACH OF LIMITED-RANDOMNESS FOUNTAIN CODES IN DEEP SPACE COMMUNICATION

Digital fountain is applied into deep space communication for its rateless and non-feedback forward error correction.However,the long code length and encoding overhead are confined factors to guarantee a considerable recovery probability as power and buffer-limited equipment in deep space environment.At the same time,the typical fountain decoding is sub-optimum decoding algorithm.We propose a new approach,Dependent Sequences Compensation Algorithm(DSCA),to improve the encoding efficiency by restricting the randomness in fountain encoding.While decoding algorithm is also optimized by redundant information in stopping set.The results show that the optimized method can obtain a 10-4 decoding failure rate with overhead under 0.20 for code length 500,which indicates the usefulness of the proposed approach in deep space communication.

China’s Lunar and Deep Space Exploration Program for the Next Decade(2020–2030)

China has carried out four unmanned missions to the Moon since it launched Chang’E-1,the first lunar orbiter in 2007.With the implementation of the Chang’E-5 mission this year,the three phases of the lunar exploration program,namely orbiting,landing and returning,have been completed.In the plan of follow-up unmanned lunar exploration missions,it is planned to establish an experimental lunar research station at the lunar south pole by 2030 through the implementation of several missions,laying a foundation for the establishment of practical lunar research station in the future.China successfully launched its first Mars probe on 23 July 2020,followed in future by an asteroid mission,second Mars mission,and a mission to explore Jupiter and its moons.

IAACS: Image aesthetic assessment through color composition and space formation

Background Determining how an image is visually appealing is a complicated and subjective task. This motivates the use of a machine-learning model to evaluate image aesthetics automatically by matching the aesthetics of the general public. Although deep learning methods have successfully learned good visual features from images,correctly assessing the aesthetic quality of an image remains a challenge for deep learning. Methods To address this, we propose a novel multiview convolutional neural network to assess image aesthetics assessment through color composition and space formation(IAACS). Specifically, from different views of an image––including its key color components and their contributions, the image space formation, and the image itself––our network extracts the corresponding features through our proposed feature extraction module(FET) and the Image Net weight-based classification model. Result By fusing the extracted features, our network produces an accurate prediction score distribution for image aesthetics. The experimental results show that we have achieved superior performance.

Timeline based autonomous mission planning system for deep space exploration

In order to realize the explorer autonomy, the software architecture of autonomous mission management system (AMMS) is given for the deep space explorer, and the autonomous mission planning system, the kernel part of this architecture, is designed in detail. In order to describe the parallel activity, the state timeline is introduced to build the formal model of the planning system and based on this model, the temporal constraint satisfaction planning algorithm is proposed to produce the explorer’s activity sequence. With some key subsystems of the deep space explorer as examples, the autonomous mission planning simulation system is designed. The results show that this system can calculate the executable activity sequence with the given mission goals and initial state of the explorer.

Ultra reliability and massive connectivity provision in integrated internet of military things(IoMT)based on tactical datalink

One of the major challenges arising in internet of military things(IoMT)is accommodating massive connectivity while providing guaranteed quality of service(QoS)in terms of ultra-high reliability.In this regard,this paper presents a class of code-domain nonorthogonal multiple accesses(NOMAs)for uplink ultra reliable networking of massive IoMT based on tactical datalink such as Link-16 and joint tactical information distribution system(JTIDS).In the considered scenario,a satellite equipped with Nr antennas servers K devices including vehicles,drones,ships,sensors,handset radios,etc.Nonorthogonal coded modulation,a special form of multiple input multiple output(MIMO)-NOMA is proposed.The discussion starts with evaluating the output signal to interference-plus-noise(SINR)of receiver filter,leading to the unveiling of a closed-form expression for overloading systems as the number of users is significantly larger than the number of devices admitted such that massive connectivity is rendered.The expression allows for the development of simple yet successful interference suppression based on power allocation and phase shaping techniques that maximizes the sum rate since it is equivalent to fixed-point programming as can be proved.The proposed design is exemplified by nonlinear modulation schemes such as minimum shift keying(MSK)and Gaussian MSK(GMSK),two pivotal modulation formats in IoMT standards such as Link-16 and JITDS.Numerical results show that near capacity performance is offered.Fortunately,the performance is obtained using simple forward error corrections(FECs)of higher coding rate than existing schemes do,while the transmit power is reduced by 6 dB.The proposed design finds wide applications not only in IoMT but also in deep space communications,where ultra reliability and massive connectivity is a keen concern.

Analysis on the deployment of mining research supported by the grant program of Deep Resources Exploration and Mining

The Deep Resources Exploration and Mining(DREAM)grant program,within the framework of The National Key Research and Development Program grants,is a pillar to implement China’s science and technology strategy in the area of deep resources exploitation.To tackle the insufficient of theories and technologies for the 1000-meter-deep mining,a section of mining,covering the research of basic theories,general technologies and application demonstration,was arranged in the layout of DREAM under the principle of"whole chain design,integrated implementation".In the aspect of basic research,DREAM mainly focused on the deep rock mechanics and mining theory,such as the in-situ mechanical behavior of deep rock,deep high stress induction and energy regulation theory.For the general and key technologies,DREAM supported the research on the mine construction and hoisting,excavation,rock breaking,mining methods and mining safety according to the characteristics of coal and metal mines.For the demonstration application,taking green,safe and efficient as the starting point,DREAM aimed at the green,safe and high efficiency mining,and the demonstration and leading role projects such as the low-waste and high-efficiency back fill mining.Since 2016,10 R&D projects have been funded,and 122 institutional participants with a total budget of RMB 235 million from the central government and RMB 480 million from enterprises as well as local governments have been involved.It is expected that the mining section of DREAM would contribute to establishing the theory and technology system in the area of deep mining and promoting the ability of deep resource exploitation in China.

Remote sensing image compression for deep space based on region of interest

A major limitation for deep space communication is the limited bandwidths available. The downlinkrate using X-band with an L2 halo orbit is estimated to be of only 5.35 GB/d. However, the Next GenerationSpace Telescope (NGST) will produce about 600 GB/d. Clearly the volume of data to downlink must be re-duced by at least a factor of 100. One of the resolutions is to encode the data using very low bit rate image com-pression techniques. An very low bit rate image compression method based on region of interest(ROI) has beenproposed for deep space image. The conventional image compression algorithms which encode the original datawithout any data analysis can maintain very good details and haven' t high compression rate while the modernimage compressions with semantic organization can have high compression rate even to be hundred and can' tmaintain too much details. The algorithms based on region of interest inheriting from the two previews algorithmshave good semantic features and high fidelity, and is therefore suitable for applications at a low bit rate. Theproposed method extracts the region of interest by texture analysis after wavelet transform and gains optimal localquality with bit rate control. The Result shows that our method can maintain more details in ROI than generalimage compression algorithm(SPIHT) under the condition of sacrificing the quality of other uninterested areas.

Development of New Capabilities Using Machine Learning for Space Weather Prediction

With the development of space exploration and space environment measurements,the numerous observations of solar,solar wind,and near Earth space environment have been obtained in last 20 years.The accumulation of multiple data makes it possible to better use machine learning technique,which has achieved unforeseen results in industrial applications in last decades,for developing new approaches and models in space weather investigation and prediction.In this paper,the efforts on the forecasting methods for space weather indices,events,and parameters using machine learning are briefly introduced based on the study works in recent years.These investigations indicate that machine learning,especially deep learning technique can be used in automatic characteristic identification,solar eruption prediction,space weather forecasting for solar and geomagnetic indices,and modeling of space environment parameters.

Jamming Monitoring Technology of the Space Situational Awareness Facilities:A Comprehensive Survey

Complicated electromagnetic environments of the space situational awareness facilities(i.e.,satellite navigation systems,radar)would significantly impact normal operations.Effective monitoring and the corresponding diagnosis of the jamming signals are essential to normal opera-tions and the innovations in anti-jamming equipment.This paper demonstrates a comprehensive survey on jamming monitoring algorithms and applications.The methods in dealing with jamming signals are summarized primarily.Subsequently,the jamming detection,identification,and direc-tion finding techniques are addressed separately.Based on the established studies,we also provide some potential trends of the demonstrated jamming monitoring issues.